使具有重复值的列在数据框中唯一 [英] Make a column with duplicated values unique in a dataframe

问题描述

我有一个数据框，其中一列具有重复的值，例如

I have a dataframe where a column has duplicate values like

employee <- data.frame(name = c('John', 'Joe', 'Mat', 'John', 'Joe'), 
            salary = c(1500, 2000, 1700, 1210, 2100), 
            startdate = c('2012-05-10', '2015-02-17', 
            '2014-09-11', '2011-11-23', '2010-10-27'))

我可以通过

unique(employee$name)

但是，我想将其中的每个项目名称列唯一。如果第二次出现某些内容，请在其后附加_1。如果再次出现，请在其后附加_2。因此，在员工数据框中，我想将第二列更改为

However, I want to make each items in the name column unique. If something appears second time append _1 to it. If it appears again append _2 to it. So, in the employee dataframe, I want to change the second column to

John
Joe
Mat
John_1
Joe_1

除了遍历它之外，还有其他方法吗？

Is there a way except looping over it?

推荐答案

我们可以将 make.names 与一起使用= TRUE 。默认情况下，。将附加在后缀数字之前，并且可以使用<$ c替换为 _ $ c> sub

We can use make.names with unique=TRUE. By default, a . will be appended before the suffix numbers, and that can be replaced by _ using sub

 employee$name <- sub('[.]', '_', make.names(employee$name, unique=TRUE))

或者建议使用更好的选择通过@DavidArenburg。如果名称列是 factor 类，则将输入列转换为字符类（<。code> as.character ），然后再应用

Or a better option suggested by @DavidArenburg. If the name column is factor class, convert the input column to character class (as.character) before applying the make.unique

 make.unique(as.character(employee$name), sep = "_")
 #[1] "John"   "Joe"    "Mat"    "John_1" "Joe_1" 

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